Efficient Content-Driven Encoding Towards a Target Video Quality

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Publisher: SMPTE — Hollywood, CA
Doc Type: Conference Paper
Content Type: Original Research
Volume: 00, pp. 1–11
Abstract: Video streaming workflows aim to maximize video quality while still maintaining smooth video streaming performance. A traditional fixed bitrate ladder consists of predetermined bitrate-resolution pairs which are optimized across a wide variety of content. Consequently, these pairs are rarely optimized for a given piece of content. Some encoding tools address this by encoding each piece of video content with many codec parameters and then evaluating the results using a video quality metric. However, this process requires significant computation which increases cost and encoding time. In this paper, we propose a novel content-driven workflow that predicts optimal encoding parameters to achieve a target perceptual video quality. We do so by designing a deep learning model that, based on the video input, predicts a VMAF rate-distortion curve. Our results indicate that such a content-driven approach is an efficient way to reduce the number of encoding attempts, minimize necessary cloud computing resources, encode most efficiently, and maximize perceptual video quality.
Publication Date: 2024-10-21
DOI: 10.5594/MOO/3048
ISBN: [object Object]
Link: https://doi.org/10.5594/MOO/3048
Author(s): Trisha Mittal
Subhadra Gopalakrishnan
Jaclyn Pytlarz
Robin Atkins
Benjamin Rolling
Gabe Russell
Keyword(s): Bitrate Ladder, Streaming, Rate-Quality Curves, Video Coding, Video Compression, Video Quality, VMAF
Copyright: © 2024 SMPTE

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Trisha Mittal, Subhadra Gopalakrishnan, Jaclyn Pytlarz, Robin Atkins, Benjamin Rolling, and Gabe Russell; Efficient Content-Driven Encoding Towards a Target Video Quality, MTS 2024, Article 37 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]. Available at https://doi.org/10.5594/MOO/3048

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Trisha Mittal, Subhadra Gopalakrishnan, Jaclyn Pytlarz, Robin Atkins, Benjamin Rolling, and Gabe Russell; Efficient Content-Driven Encoding Towards a Target Video Quality, MTS 2024, Article 37 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]. Available at https://doi.org/10.5594/MOO/3048

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<span class="citation">Trisha Mittal, Subhadra Gopalakrishnan, Jaclyn Pytlarz, Robin Atkins, Benjamin Rolling, and Gabe Russell; <cite>Efficient Content-Driven Encoding Towards a Target Video Quality</cite>, MTS 2024, Article 37 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]. Available at <a href="https://doi.org/10.5594/MOO/3048" target="_blank" rel="noopener">https://doi.org/10.5594/MOO/3048</a></span>

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<li>
Trisha Mittal, Subhadra Gopalakrishnan, Jaclyn Pytlarz, Robin Atkins, Benjamin Rolling, and Gabe Russell; <cite id="bib-10-5594-moo-3048">Efficient Content-Driven Encoding Towards a Target Video Quality</cite>, MTS 2024, Article 37 (pp. 1 to 11); SMPTE, 2024, ISBN: [object Object]
<span class="doi">10.5594/MOO/3048</span>
</li>